arXiv subjects

Thomas Carreau

Publications and source records attributed to Thomas Carreau.

4 recordsLinked to original sources

arXiv2026

SINAPSE: A lightweight deep learning framework for accurate and explainable neutron-$\gamma$ discrimination

Traditionally, neutron-$\gamma$ discrimination in organic scintillators relies on techniques such as time-of-flight (ToF) selection and pulse-shape discrimination (PSD). However, particle identification through graphical cuts remains challenging in the low-charge regime due to poor signal-to-noise ratios (SNR). In this work, we propose SINAPSE, a lightweight deep learning framework for accurate and explainable neutron-$\gamma$ discrimination in the low-charge regime. The framework employs a dual-branch architecture that combines a 1-dimensional convolutional autoencoder for waveform denoising with a classifier for particle identification. Random augmentations are applied to high-SNR waveforms to simulate low-charge conditions, enabling robust extrapolation into regimes where conventional PSD labels are unreliable. We show that SINAPSE achieves superior denoising performance compared to conventional digital signal processing techniques, and outputs well-calibrated probabilities, consistent with traditional graphical cuts. Finally, we apply SHAP (SHapley Additive exPlanations) values to show that model decisions are driven by physically meaningful pulse-shape features, confirming consistency with established PSD principles.

physics.ins-det↗

arXiv2019

Bayesian analysis of the crust-core transition with a compressible liquid-drop model

The crust-core phase transition of neutron stars is quantitatively studied within a unified meta-modelling of the nuclear Equation of State (EoS). The variational equations in the crust are solved within a Compressible Liquid Drop (CLD) approach, with surface parameters consistently optimized for each EoS set on experimental nuclear mass data. When EoS parameters are taken from known Skyrme or RMF functionals, the transition point of those models is nicely reproduced. A model-independent probability distribution of EoS parameters and of the transition density and pressure is determined with a Bayesian analysis, where the prior is given by an uncorrelated distribution of parameters within the present empirical uncertainties, and constraints are applied both from neutron star physics and ab-initio modelling. We show that the characteristics of the transition point are largely independent of the high density properties of the EoS, while ab-initio EoS calculations of neutron and symmetric matter are far more constraining. The most influential parameter for the determination of the transition point governs the surface properties of extremely neutron rich matter, and it is strongly unconstrained. This explains the large dispersion of existing predictions of the transition point. Only if the surface tension is fixed to a reasonable but somewhat arbitrary value, strong correlations with isovector parameters ($L_{sym},K_{sym}$ and $Q_{sym}$) are recovered. Within the present experimental and theoretical uncertainties on those parameters, we estimate the transition density as $n_t= 0.072\pm 0.011$ fm$^{-3}$ and the transition pressure as $P_t=0.339\pm0.115$ MeV fm$^{-3}$.

nucl-th↗

arXiv2019

General predictions for the neutron star crustal moment of inertia

The neutron star crustal EoS and transition point properties are computed within a unified meta-modeling approach. A Bayesian approach is employed including two types of filters: bulk nuclear properties are controlled from low density effective field theory (EFT) predictions as well as the present knowledge from nuclear experiments, while the surface energy is adjusted on experimental nuclear masses. Considering these constraints, a quantitative prediction of crustal properties can be reached with controlled confidence intervals and increased precision with respect to previous calculations: {$\approx 11\%$} dispersion on the crustal width and {$\approx 27\%$} dispersion on the fractional moment of inertia. The crust moment of inertia is also evaluated as a function of the neutron star mass, and predictions for mass and radii are given for different pulsars. The possible crustal origin of Vela pulsar glitches is discussed within the present estimations of crustal entrainment, disfavoring a large entrainment phenomenon if the Vela mass is above $1.4M_\odot$. Further refinement of the present predictions requires a better estimation of the high order isovector empirical parameters, e.g. $K_{sym}$ and $Q_{sym}$, and a better control of the surface properties of extremely neutron rich nuclei.

nucl-th↗

arXiv2019

Quantifying the uncertainties on spinodal instability in stellar matter through meta-modeling

The influence of the uncertainties of the equation of state empirical parameters on the neutron stars crust-core phase transition is explored within a meta-modeling approach, in which the energy per particle is expanded as a Taylor series in density and asymmetry around the saturation point. The phase transition point is estimated from the intersection of the spinodal instability region for dynamical fluctuations with the chemical equilibrium curve. Special attention is paid to the inclusion of high-order parameters of the Taylor series and their influence on the transition point. An uncorrelated prior distribution is considered for the empirical parameters, with bulk properties constrained through effective field theory predictions, while the surface parameters are controlled from a fit of nuclear masses using the extended Thomas Fermi approximation. The results show that the isovector compressibility $K_{sym}$ and skewness $Q_{sym}$ have the most significant correlations with the transition point, along with the previously observed influence of the $L_{sym}$ parameter. The estimated density and pressure of the crust-core transition are $n_t = (0.071 \pm 0.011) fm^{-3}$ and $P_t = (0.294 \pm 0.102) MeV fm^{-3}$.

nucl-th↗